Abstract 17103: The Proteomic Fingerprint in Patients With Single Ventricle Disease in the Interstage Period: Evidence of Chronic Inflammation and Widespread Activation of Biological Networks

Abstract

Introduction: Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time: (AKI 70%, neurodevelopmental impairment 33%, growth failure 14%, NEC 5.5%). Proteomics is a novel method to identify new biomarkers and mechanisms of injury in complex physiologic states. Hypothesis: Does the proteome of patients with SVHD differ from healthy children, and which biological systems are activated or repressed? Methods: Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at -80C, and run on a panel of 1500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR < 0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. Results: PLS-DA readily discriminated between cases (n=33) and controls (n=24) based on their proteomic pattern alone (Accuracy=0.96, R2=0.97, Q2=0.80) (Fig 1a). 568 proteins differed between groups (FDR < 0.05). The 15 proteins with the greatest effect on the proteomic phenotype between the groups are shown (Fig 1b). We identified 25 up-regulated functional clusters and 13 down-regulated (5 clusters highlighted in Fig 1c). Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neuronal development, gastrointestinal system, and cardiac development. Conclusions: We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with >500 circulating proteins distinguishing the groups. This proteomic data identifies various dysregulated protein networks across multiple organ systems with promising biological plausibility as drivers of SVHD morbidity.